---
title: "  "
output: 
  flexdashboard::flex_dashboard:
    logo:
    theme : flatly
    social: menu
    source_code: embed
    orientation: columns
    vertical_layout: fill
   
---

```{r setup, include=FALSE}
#------------------ Packages ------------------
library(flexdashboard)
library(tidyverse)
#------------------------------------------------------------------------------
ZLK1=read_csv("data/data.soya.csv")
ZLK1=dplyr::arrange(ZLK1, ZLK1$Fecha) # ordena la serie  por fecha
ZLK1=distinct(ZLK1) # elimina duplicados
d1=dim(ZLK1)        # dimension de la serie
ud1=ZLK1[d1[1],]    # ultimo registro
# ud1=ZLK1[1,]
#------------------------------------------------------------------------------
dir2="data/tasa_USD_COP.csv"
dir3= "data/Datos históricos S&P 500.csv"
dir4= "data/Datos históricos Futuros petróleo crudo WTI.csv"
dir5="data/Datos históricos DIA.csv"
#------------------------------------------------------------------------------
# funciones para graficos
#-----------------------------------------------------------------------
# grafico de la serie
grafico1=function(file){
  fig.oil.s1=ggplot(file, aes(x = Fecha, y =cierre)) +
    geom_line(color = "#FC4E07", size = 1)
  ggplotly(fig.oil.s1) 
}

#-----------------------------------------------------------------------
#grafico con tendencia
grafico2=function(file){
  fig.oil.s0=ggplot(file, aes(Fecha, cierre)) + 
    geom_line(color = "#FC4E07", size = .5) +
    geom_smooth(method = "loess", se = FALSE, span = 0.05)
  ggplotly(fig.oil.s0)
}

#-----------------------------------------------------------------------
#grafico con pronosticos arima
grafico3=function(file){
  p.arima1=auto.arima(file$cierre,stepwise = FALSE, approximation = FALSE)
  f.arima1=forecast(p.arima1,h=14,level=95)
  fig.oil.s2=ggplot(file, aes(Fecha, cierre)) + 
    geom_line(color = "#FC4E07", size = .5) +
    geom_line(aes(y=f.arima1$fitted),color = "#00AFBB", size=0.5) 
  ggplotly(fig.oil.s2)
}
#-----------------------------------------------------------------------
# tabla estimacion semana siguiente
pronosticos=function(file){
  p.arima1=auto.arima(file$cierre,stepwise = FALSE, approximation = FALSE)
  f.arima1=forecast(p.arima1,h=14,level=c(95))
  knitr::kable(f.arima1$lower, align = "rr")
}
#-----------------------------------------------------------------------
# paquetes a utilizar ==========================================================

# install.packages("quantmod", dependencies = TRUE)
# install.packages("readxl", dependencies = TRUE)
# install.packages("hrbrthemes")
# install.packages("plotly")
# install.packages("dygraphs")

library(tidyverse)
library(quantmod)
library(readxl)
library(dplyr)
library(hrbrthemes)
library(plotly)
library(dygraphs)
library(forecast)
library(colortools)
library(stringr)
library(lubridate)
library(rvest)
library(xts)
library(zoo)
#===============================================================================

```


ZLK1
=======================================================================
Column { data-width=50 }
-----------------------------------------------------------------------
### apertura  {.value-box}
```{r}
valueBox(value = ud1$apertura, 
         caption = "apertura", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```


### cierre  {.value-box}
```{r}
valueBox(value = ud1$cierre, 
         caption = "cierrre", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```


### minimo  {.value-box}
```{r}
valueBox(value = ud1$min, 
         caption = "minimo", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```


### maximo {.value-box}
```{r}
valueBox(value = ud1$max, 
         caption = "maximo", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```

### variacion  {.value-box}
```{r}
valueBox(value = ud1$var, 
         caption = "variacion", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```


### volumen  {.value-box}
```{r}
valueBox(value = paste(ud1$vol,"K"), 
         caption = "volumen", 
         icon = "fa-line-chart", 
         color = "#3cb371")
```



Column { data-width=1000 }
-----------------------------------------------------------------------
```{r, fig.dim=c(14,7)}
grafico1(ZLK1)
```





Tendencia
=======================================================================
Column { data-width=900 }
-----------------------------------------------------------------------

```{r, fig.dim=c(14,7)}
grafico2(ZLK1)
```


Pronósticos
=======================================================================
Column { data-width=800 }
-----------------------------------------------------------------------
```{r, fig.dim=c(13,7)}
grafico3(ZLK1)
```



Column { data-width=200}
-----------------------------------------------------------------------
### Pronosticos proximos dias
```{r}
# pronosticos(ZLK1,14)

```




Datos
=======================================================================

Column { data-width=400 }
-----------------------------------------------------------------------
```{r}
d=dim(ZLK1)
DT::datatable(psych::headTail(ZLK1,d[1] ),fillContainer = FALSE, options = list(pageLength = 15))
```
Column { data-width=200 }
-----------------------------------------------------------------------

```{r}
# pronosticos1(ZLK1,14)
```
Column { data-width=200 }
-----------------------------------------------------------------------


Indicadores
=======================================================================
Column {.tabset}
-----------------------------------------------------------------------

### petróleo crudo WTI
```{r, fig.dim=c(14,2)} 
#  fig.i1=ggplot(tasa.USD.COL, aes(Fecha, cierre)) + 
#  geom_line(color = "#0080bb", size = 1) 
#  ggplotly(fig.i1)
```

-----------------------------------------------------------------------

### Dow Jones Ind.
```{r, fig.dim=c(14,2)}
# fig.i2=ggplot(Dow.Jones, aes(Fecha, cierre)) + 
#  geom_line(color = "#004145", size = 1) 
# ggplotly(fig.i2)
```

-----------------------------------------------------------------------

### USD/COP
```{r, fig.dim=c(14,2)}
# fig.i3=ggplot(tasa.USD.COL, aes(Fecha, cierre)) + 
#  geom_line(color = "#0052bb", size = 1)
# ggplotly(fig.i3)
```

###  S&P   
```{r, fig.dim=c(14,2)}
# fig.i3=ggplot(SyP.500, aes(Fecha, cierre)) + 
#  geom_line(color = "#0052bb", size = 1)
# ggplotly(fig.i3)
```

Información
=======================================================================
```{r}

```


Información 
=======================================================================